ggplotly(
ggplot(covid_death_sdf1) +
geom_sf(aes(fill = incidence)) +
theme(legend.text = element_text(size = 6),
legend.position = 'right', axis.text.x = element_text(angle = 45)) +
labs(
title = "Covid-19 Cumulative Incidence \n March - September 2020 by ZCTA",
x = "Latitude",
y = "Longitude", fill = "Covid-19 Cumulative Incidence\n (Cases/100,000)"))
covid_death_sdf = st_read("deathrate_map1.shp")
## Reading layer `deathrate_map1' from data source
## `/Users/tanyabutt/Desktop/Data Science/p8105_finalproject/website/deathrate_map1.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 178 features and 22 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -74.25559 ymin: 40.49612 xmax: -73.70001 ymax: 40.91553
## Geodetic CRS: WGS 84
fig <- ggplotly(
ggplot(covid_death_sdf) +
geom_sf(aes(fill = cum_death)) +
theme(legend.text = element_text(size = 6),
legend.position = 'right', axis.text.x = element_text(angle = 45)) +
labs(
title = "Cumulative Moraltiy Rate \n March - September 2020 by ZCTA",
x = "Latitude",
y = "Longitude", fill = "Cumulative Mortality Rate\n (Deaths/100,000)"))
fig
fig <- ggplotly(
ggplot(covid_death_sdf1) +
geom_sf(aes(fill = pro_offers)) +
theme(legend.text = element_text(size = 6),
legend.position = 'right', axis.text.x = element_text(angle = 45)) +
labs(
title = "Proportion of SHSAT Offers\n in 2020 by ZCTA",
x = "Latitude",
y = "Longitude", fill = "Proportion of SHSAT Offers"))
fig
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